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Record W791123359 · doi:10.4148/2378-5977.1630

Grazing cattle on winter cereal pasture on the sandy soils of south-central Kansas

2004· article· en· W791123359 on OpenAlexaff
V. L. Martin, Richard Hale

Bibliographic record

VenueKansas Agricultural Experiment Station Research Reports · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsFields Institute for Research in Mathematical Sciences
Fundersnot available
KeywordsPastureAgronomyTriticaleHayForageAcreSorghumGrazingStockingBiologyHectareAnimal scienceAgriculture

Abstract

fetched live from OpenAlex

Rye, wheat, and triticale pasture were evaluated during the winters of 2000-01, 2001-02, and 2002-03 for their ability to increase cattle weight from late fall through mid-spring. Large-scale studies were conducted on two 80-acre sites divided into either 25- or 40-acre pastures. Cattle at these sites were stocked at one head per acre, with an average initial weight between 500 and 550 lb. At the Sandyland Experiment Field, small-scale studies were conducted by using the same winter cereals for forage, but at greater stocking rates, ranging from two to three head per acre. Supplemental feeding, as necessary, included summer annual forage hay, prairie hay, and grain consisting of wheat middlings and processed grain sorghum. Winter cereals were planted at 100 lb/acre in September of each year. Rye provided the best pasture in terms of cattle weight gain and needed the least supplemental feeding. Wheat was next in producing pounds of beef, and triticale produced less gain than either rye or wheat. These data suggest that rye and wheat were able to support greater stocking rates than triticale.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.319
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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